Archive for the ‘Women in Engineering’ Category

Tech startups have special challenges. Founders need to keep an eye on technology disruption, they have to find, recruit and keep the best talent, and they have to stay ahead of their competition. In the early stages there are no funds and never enough resources or time. In spite of this tech startup founders find a way to stand up their first product and land their first customers.

Join us for an afternoon with tech startup founders Melinda Jacobs, Cofounder, Lucent Sky, Maria Karam, Founder, Tactile Audio Displays Inc and the Inventor’s Nest, and Eddy Song Fonder of Inlighten Co as they share their own stories of the early stages of their businesses.

Come and hear how they do it and how they turn their ideas into products customers want.

Biography: Melinda Jacobs is cofounder of Lucent Sky, an application security vendor based in San Francisco and Taipei. Originally from Fredericton, Melinda studied as a Loran Scholar at the University of Toronto and currently serves on the Board of Directors of the University of Toronto Alumni Association (UTAA). Last year Melinda presented a keynote at the Lean Startup conference in San Francisco and is a frequent presenter on social entrepreneurship, security and risk. She was recently named a Senior Fellow of the Canadian International Council and now resides in Toronto.

Dr. Karam is the inventor and President of Tactile Audio Displays inc., and a Senior visiting research fellow at Kings College London UK. Dr. Karam’s specializes in the research and development of tactile communication systems and multi sensory technology integration in luxury autonomous vehicles, accessibility, and immersive entertainment environments. Maria is also the founder of the Inventors Nest, a new innovation and collaboration hub for artists, scientists, and techies. (please shorten or select the parts you think are relevant). I have also been a member of the IEEE since 2005.

Eddy Song is the founder of Inlighten Co. Inlighten makes fashionable clothing from fibre optic textiles. Their first products are popular with the EDM community.

Abstract: Blockchain protocol and technology are said by many to be among the greatest accomplishments of human intellect since the Internet. Blockchain is the software technology underlying what is commonly known as Bitcoin, however, the technology is not exclusive to Bitcoin. Swarms of innovators are working feverishly to design and deploy new business platforms that incorporate blockchain technology.

In this session, we learn about the concepts of cryptocurrency and blockchain, what are the potential for this technology and when a blockchain solution would be applicable to an enterprise.

Biography: Omid Sadeghi is a serial entrepreneur and technology advisor with domain expertise in commercialization and developing customer-centric products. Omid holds an undergraduate degree in Design Engineering and an MBA degree from Schulich School of business (Winner of more than $40,000 student awards).

He is the director of BlockchainHub at York University to connect Research, education, and commercialization in Blockchain space. BlockchainHub currently run numerous educational programs and run various projects including setting up a state of the art Blockchain-based certification system for York University.

Omid is active in building and supporting technology and engineering communities, especially in Toronto. He is on the advisory board of different blockchain initiatives and a board member of Professional Engineers of Ontario-ETC.

Join us on November 7 to hear about the work of Dr. AJung Moon, founder and CEO of Generation R, and founder and Director of the Open Roboethics Institute (ORI). Dr. Moon has been speaking and advising internationally on roboethics issues since 2012. Her company, Generation R is the first consulting firm in the world to deliver ethics assessments of predictive algorithms for today’s businesses.

Come and hear about her experiences working with the private sector, helping them assess their ethical risk as they implement these advanced technologies.

Day & Time: Tuesday, November 7th, 2017
6:30 p.m. to 9:00 p.m.

Speaker: Dr. AJung Moon
Founder and CEO of Generation R
Founder and Director of the Open Roboethics Institute (ORI)

Abstract: Ethics is increasingly becoming a buzz word in AI and robotics. Machine learning algorithms and robotics systems have been developed and used for years, but never before has the discussion about ethics of the technologies been getting so much attention. What is all this AI ethics and roboethics discussion all about? What ethical risks do you and your organization end up (often unknowingly) taking on as you increasingly implement machine autonomy into your organization? Most importantly, what can you do about them? Small and large companies today are struggling to innovate their operations with data-driven, predictive algorithms without the full understanding of what undesirable effects these algorithms can have on their organization and our society. As applications of robotics extend to areas outside of industrial environments, roboticists are increasingly noticing the importance for designers and policy makers to address the question of “What should a robot do?” It turns out that discussions about ethics becomes quite sexy when mixed with autonomous, intelligent technologies.

Dr. Moon will share relevant studies and examples (from right here in Canada!) to paint a broad landscape of the fascinating world of AI ethics and roboethics.

Biography: Dr. AJung Moon is a roboticist on a mission to make ethics a core part of AI and robotics technologies. She is a founder and CEO of Generation R, the first consulting firm in the world to deliver ethics assessment of predictive algorithms for today’s businesses. She is also a founder and Director of the Open Roboethics Institute (ORI), an international think tank that has been spearheading open discussions on roboethics topics since 2012. She holds a PhD in Mechanical Engineering (Vanier Scholar) from the University of British Columbia with a specialization in the design of human-inspired interactive robot behaviours and roboethics.

She advises numerous national and international organizations on ethical and societal implications of AI and robotics, including the OECD, ICRC, and the United Nations Convention on Conventional Weapons. She serves on the Executive Committee of The IEEE Global Initiative for Ethical Considerations in AI and Autonomous Systems and served as a founder and co-chair of the IEEE Global Initiative’s committee on embedding values into autonomous intelligent systems. She is a co-chair of the Canadian Robotics Strategy, and a panelist of the International Panel on the Regulation of Autonomous Weapons (IPRAW). Now she is excited to be on the program committee of the new, AAAI/ACM Conference on AI, Ethics, and Society.

You probably know all about the Arduino open-source electronics prototyping platform already. Maybe you’ve used one before or perhaps you’re just interested in getting your hands on one to see just how innovative you can be. Now’s your chance!

Register for the Arduino Workshop and you could soon be exploring the powerful capabilities of Arduino, with a Thales expert on hand to show you the ropes, and the chance to win some great prizes including a fitbit altaHR and the opportunity to visit a Thales Research Centre in one of the participating regions.

Abstract: Histological staining, interpreted by a pathologist, has remained the gold standard for cancer diagnosis and staging for over 100 years. There is a growing need for better – and more personalized – cancer treatments, to provide oncologists with the tools they need to best treat their patients. The advent of “molecular medicine”, or targeted therapeutic strategies that rely on knowledge of particular mutations in a cancer in order to tailor treatment, has improved cancer therapy for many patients. This has led to the use of companion diagnostics, in which tumor biopsies are stained for a specific marker or set of markers, using immunohistochemical approaches. The information obtained from the degree of staining or spatial arrangement of stained cells within the tumor helps to identify tumor molecular subclasses that may benefit from such tailored therapeutic approaches.

The increase in the number of slides being stained for specific markers and used in diagnosis, along with the increased need for quantitative assessment of the degree of staining, number of cells, or spatial arrangement of cells within the tumor, has increased the volume and type of work that pathologists encounter in their diagnostic workflow. Our team works on the development of tools for quantitative digital pathology analysis that can benefit pathologists, by building and validating semi-automated algorithms for cellular quantification and intensity scoring of stained slides. We use machine learning methods to learn features that distinguish different morphological regions from pathologist annotations. These are then fed into a tissue segmentation and classification framework to break the tissue down into its components, either on the individual cell level, or the glandular level. Staining intensity is quantified following colour deconvolution of the individual stain components, and reporting metrics are designed, in close collaboration with pathologists and biological scientists, to identify the appropriate outputs for comparing between treatment groups or different cancer types.

The use of multiplexed digital pathology stains allows us to build a generalized analytical framework to perform “tissue cytometry”. This new technology can extract quantitative image-derived features in a reproducible and robust fashion, providing clinicians and biological scientists with tools to measure previously inaccessible phenomena, like measuring the hypoxic gradient directly within tumor sections, or comparing glucose uptake to lactic acid production in the same tumor sample. This approach establish the foundation for a bridge between traditional morphometric assessment of tumor biopsies, and the detailed spatially resolved chemical and molecular content maps of each tumor, providing an invaluable toolkit for the discovery of cancer molecular subtypes, and development of therapeutic interventions.

Biography: Dr. Trevor McKee received his Ph.D. in Biological Engineering from the Massachusetts Institute of Technology in 2005, in the laboratory of Dr. Rakesh Jain of Harvard Medical School. During his graduate work, he pioneered the application of new imaging and analysis technologies to studying drug transport within tumors, and on developing methods to improve drug delivery. He also holds a Bachelors of Science in Chemical Engineering with a Biotechnology minor from the University at Buffalo. He moved to Toronto to continue postdoctoral work at the Ontario Cancer Institute, applying multi-modality imaging and quantitative image analysis methods to study preclinical cancer models. He has a successful track record of high-impact publications with a number of clinical and basic science collaborators, and has also collaborated with pharmaceutical companies on imaging-based preclinical testing of new compounds. He is currently Image Analysis Core Manager of the STTARR Innovation Centre, and manages a team of analysts to develop new algorithms for machine-learning powered image segmentation and quantification across a number of disease sites. His research interests lie in studying the tumor microenvironment, drug and oxygen delivery, and the development of tools for “tissue cytometry” – deriving complex biological and spatial relationships from tissue sections via computational image analysis methods.

Abstract: The scale of data being generated in medicine and research can easily overwhelm typical analytic capabilities. This is particularly true with MRI/fMRI scanning, genomics data, streaming/wearables data in addition to other clinical data types, especially if in combination.

Challenges include 1) large file sizes often in heterogeneous formats 2) currently no standard Protocol exists for extraction of standardized characteristics, and 3) traditional methods for group-wise comparison can often result in spurious findings.

The talk will address these challenges by discussing customized processing pipelines built for multiple data types in biomedicine, which enable effective machine learning and other types of analytics on these datasets. This approach leverages the rapid model building capabilities of our real-time machine learning software to iterate through normalization parameters for each data type and disease class. In addition, this platform allows easy integration between the various medical data types (genome sequence, phenotypic, and metabolic data) allowing generation of more comprehensive disease classification models.

The ability to standardize and pre-process multiple types of biomedical data for machine learning, no matter the source and type, and effectively combine it with other data types is a powerful capability and holds promise for the future of diagnostics and precision medicine.

Biography: Shiva Amiri is the CEO of BioSymetrics Inc. where they are developing a unique real-time machine learning technology for the analysis of massive data in biomedicine. BioSymetrics specializes in providing optimized pipelines for complex data types and effective methods in the analytics of integrated data. Prior to BioSymetrics she was the Chief Product Officer at Real Time Data Solutions Inc., she has led the Informatics and Analytics team at the Ontario Brain Institute, where they developed Brain-CODE, a large-scale neuroinformatics platform across the province of Ontario. She was previously the head of the British High Commission’s Science and Innovation team in Canada. Shiva completed her Ph.D. in Computational Biochemistry at the University of Oxford and her undergraduate degree in Computer Science and Human Biology at the University of Toronto. Shiva is involved with several organisations including Let’s Talk Science and Shabeh Jomeh International.

Wednesday May 31, 2017 at 6:00 p.m. hear about the work of Dr. Sanja Fidler, Assistant Professor in Machine Learning and Computer Vision, University of Toronto and Dr. Inmar Givoni, Director of Machine Learning at Kindred Systems Inc., as part of “Women in Robotics: Building Smart Robots with AI”.

Get Your Bot On!, its partners Society of Women Engineers Toronto, IEEE Toronto Engineering in Medicine and Biology Society (EBMS) and IEEE Women in Engineering are pleased to bring you the ‘Women in Robotics Speaker Series’. This series celebrates the work of women in the field of robotics and provides a forum for them to share their work and career with the community. We invite all community members to come and learn, participate in the discussion, and celebrate the contribution of women to this field.

Dr. Sanja Fidler is an Assistant Professor at the Department of Computer Science, University of Toronto. She is the recipient of the Amazon Academic Research Award (2017) and the NVIDIA Pioneer of AI Award (2016). Previously she was a Research Assistant Professor at TTI-Chicago a philanthropically endowed academic institute located in the campus of the University of Chicago. She completed her PhD in computer science at University of Ljubljana in 2010, and was a postdoctoral fellow at University of Toronto during 2011-2012.

In 2010 she visited UC Berkeley. She has served as a Program Chair of the 3DV conference, and as an Area Chair of CVPR, EMNLP, ICCV, ICLR, and NIPS. Together with Rich Zemel and Raquel Urtasun, she received the NVIDIA Pioneer of AI award.

Her main research interests are object detection, 3D scene understanding, and the intersection of language and vision.

Dr. Inmar Givoni is the Director of Machine Learning at Kindred, where her team develops algorithms for machine intelligence, at the intersection of robotics and AI. Prior to that, she was the VP of Big Data at Kobo, where she led her team in applying machine learning and big data techniques to drive e-commerce, customer satisfaction, CRM, and personalization in the e-pubs and e-readers business. She first joined Kobo in 2013 as a senior research scientist working on content analysis, website optimization, and reading modelling among other things. Prior to that, Inmar was a member of technical staff at Altera (now Intel) where she worked on optimization algorithms for cutting-edge programmable logic devices.

Inmar received her PhD (Computer Science) in 2011 from the University of Toronto, specializing in machine learning, and was a visiting scholar at the University of Cambridge. During her graduate studies, she worked at Microsoft Research, applying machine learning approaches for e-commerce optimization for Bing, and for pose-estimation in the Kinect gaming system. She holds a BSc in computer science and computational biology from the Hebrew University in Jerusalem. She is an inventor of several patents and has authored numerous top-tier academic publications in the areas of machine learning, computer vision, and computational biology. She is a regular speaker at big data, analytics, and machine learning events, and is particularly interested in outreach activities for young women, encouraging them to choose technical career paths.

Friday May 26, 2017 at 1:30 p.m. Dr. Sergio A. A. Freitas, Associate Professor in the Gama Engineering College (FGA) and Director of the Distance Education Center at the University of Brasilia (UnB), Brazil, will be presenting “Designing a Gamification Course for an Higher Education Audience”.

Abstract: The gamification of activities in classrooms has become of great interest in higher education. Today’s students have a lot of experience in virtual environments and games, and researchers who have tested/used gamification in their classrooms have reported an increase in student engagement and retention.

At the end of the workshop it is expected that the participant will be able to design a basic gamified course.

Biography: Dr. Sergio A. A. Freitas is currently an Associate Professor in the Gama Engineering College (FGA) and Director of the Distance Education Center at the University of Brasilia (UnB), Brazil. He is also the coordinator of research in the FGA Software Factory Laboratory. His current research projects focus on interdisciplinary studies and applications of learning methodologies on engineering undergraduate courses, and software engineering methodologies. Prof. Freitas areas of expertise include gamification, PBL, virtual learning environments in education and training, and software engineering methodologies. Dr. Freitas has coauthored journal publications, conference articles and book chapters in the aforementioned topics, and has coordinated and participated on many projects from various funding agencies CNPq, FAP-ES, FAP-DF, Cebraspe, and Brazilian Federal Ministries.

Friday May 12, 2017 the School of Engineering Technology and Applied Science and the Centennial Energy Institute invite you to our 2017 E3 Symposium: The Future is Smart: The Transformation of Canadian Manufacturing. This event will bring together advanced manufacturing innovators from across a number of sectors in the economy. The event will feature industry titans sharing best practices.